Semantic Spatial Web
A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).
Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 24588
Special Issue Editors
Interests: data governance; AI governance; knowledge graphs; data quality; data value; data privacy
Special Issues, Collections and Topics in MDPI journals
Interests: NLP for the semantic web; ontology based information extraction; semantic annotation; natural language generation
Interests: ontologies; knowledge graph engineering; knowledge management; knowledge learning; data quality; linked data; Internet of Things
Special Issue Information
Dear Colleagues,
Spatial data are vital for many application scenarios, such as navigation, logistics, and tourism. The last decade has seen a steady increase in geospatial linked data deployment. Large numbers of linked data datasets contain geospatial aspects (e.g., DBpedia, Wikidata), and there is increasing deployment of Linked Data for national geospatial infrastructure (e.g., Geohive in Ireland, Kadaster in the Netherlands) and now in the Architecture, Engineering and Construction (AEC) sector and for Internet of Things deployments. New applications integrating geospatial linked data into public and private organizations have immense potential for a social, economic, and scientific impact. Geospatial linked data allow discovery and access using the standard mechanisms of the Web and simplify the process of generating interoperable geospatial infrastructure. This is especially relevant to delivering the promise of the INSPIRE directive in Europe. Moreover, geospatial information systems benefit from linked data principles in building the next generation of spatial data applications, such as federated smart buildings and self-piloted vehicles.
The goal of this Special Issue is to provide an opportunity for the geospatial linked data community to focus on the emerging need for effective and efficient production, management, and utilization of geospatial information as linked data. Emphasis will be given to works describing novel methodologies, algorithms, and tools that advance the current state-of-the-art with respect to efficiency or effectiveness. Thus, we invite papers related to the challenges and solutions proposed to deal with geospatial linked data, especially for building high-quality, adaptable, geospatial infrastructures and novel applications. We aim at demonstrating the latest approaches and implementations, as well as discussing solutions to the challenges and issues arising from research and industrial organizations.
- Spatial linked data vocabularies and standards (GeoSPARQL, INSPIRE, W3C, OGC, ISO)
- Extraction/transformation of geospatial linked data from native geospatial data sources
- Integration (schema mapping, interlinking, fusion) techniques for geospatial RDF data
- Enrichment, quality, and evolution of linked data with spatial information
- Machine learning improving geospatial linked data processing
- Distributed solutions for geospatial linked data management (storing, querying, mapping)
- Algorithms and tools for large scale, scalable geospatial linked data management
- Efficient indexing and querying of geospatial linked data
- Geospatial-specific reasoning on RDF data
- Ranking techniques on querying geospatial RDF data
- Advanced querying capabilities on geospatial RDF data
- Benchmarking of geospatial linked data applications
- Geospatial linked data in social web platforms and applications
- Visualization models/interfaces for browsing/authoring/querying geospatial linked data
- Natural language processing (NL) applications for the spatial semantic web
- Ontology based information extraction and semantic annotation for geospacial semantic web
- Linking entities in content to geospatial linked data
- Natural language interfaces to geospatial linked data (creating, querying and accessing geospatial RDF data)
- Real-world applications/use cases/paradigms using geospatial linked data
- Evaluation/comparison of tools/libraries/frameworks for geospatial linked data
- Data governance models for geospatial linked data
- Building information modeling for building life cycle (GIS data, geographical data, and so forth)
- Linking building data to geospatial linked data
- Architectural and construction data for geospatial linked data
- Geospatial linked data for smart cities
- Crowdsourced spatial linked data
Dr. Rob Brennan
Dr. Brian Davis
Dr. Armin Haller
Dr. Beyza Yaman
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- spatial/geospatial linked data
- geospatial data quality
- geospatial data standards
- NLP applications for spatial data
- architecture
- engineering and construction
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